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Pixel-global Self-supervised Learning with Uncertainty-aware Context Stabilizer
Moreover, we used Monte Carlo dropout in the stabilizer to measure uncertainty and adaptively balance the discrepancy between the representations of the same pixels in different views.
Weaving Attention U-net: A Novel Hybrid CNN and Attention-based Method for Organs-at-risk Segmentation in Head and Neck CT Images
Our results of the new Weaving Attention U-net demonstrate superior or similar performance on the segmentation of head and neck CT images.
Pyramid Medical Transformer for Medical Image Segmentation
Deep neural networks have been a prevailing technique in the field of medical image processing.
Semi-supervised Semantic Segmentation of Prostate and Organs-at-Risk on 3D Pelvic CT Images
We developed a novel semi-supervised adversarial deep learning approach for 3D pelvic CT image semantic segmentation.
ARPM-net: A novel CNN-based adversarial method with Markov Random Field enhancement for prostate and organs at risk segmentation in pelvic CT images
A segmentation network and a discriminator network were trained jointly, and only the segmentation network was used for prediction.
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